Rabimba Karanjai

Biography

Full Time Graduate Researcher, part time hacker and FOSS enthusiast.

I used to write code for Watson and do a bunch of other things at their lab (mostly deals with algorithm,NLP, Ontologies,reading papers among other stuff). At present intern at Almaden Research Center. And crawling my way towards a PhD at RICE University.

Open Source Bridge 2017

Sessions for this user

Virtual Reality is on the rise. We keep seeing new devices and frameworks who promises to get the job done. All of them work and are awesome. But all of them are proprietary, binds you to their ecosystem and their expensive hardware. Not to mention they are not cross-platform, don't run on other devices and the curve to learn the technology is too high.
What if we can get out of this walled garden? Build everything in open web technologies, run instantly in any device and still be able to enjoy similar experience? And can learn to build our own virtual world in a 45 mins session?
Meet aframe and Web Virtual Reality

Open Source Bridge 2016

Sessions for this user

People are already tired of the over-promise of IoT - the slew of marginally useful products, the overly confusing and crowded developer space, and endless examples of how to turn an LED on and off.
Take a break, step back from the crowd, and come learn how to solve real human problems with that old phone that's collecting dust on your shelf.

Proposals for this user

We will explore how we can utilize webvr to build amazing VR experience right into everyone's pocket, using their mobile phones they use right now. No need for expensive or closed source tools or solutions. Utilize the mobile phone with cardboard and uisng just javascript and html to build VR world. How using api's of webvr and Aframe we game developers and UI builders can build awesome experience.

Open Source Bridge 2015

Sessions for this user

Language input for mobile devices has always been a challenge on how to provide intuitive experience along with the easy of type. One approach towards that end is predictive text input. But predictions are as good as the wordlist that it gets generated from. Often it becomes a much harder problem to implement the same approach for localized languages like Hindi,Bengali (India, Bangladesh) and languages that require IME to type effectively. One approach is to learn from users typing preference and improve the dictionary weight-age to improve prediction. This talk will discuss upon how this can be implemented in Firefox OS and how the same approach can be used for openweb apps universally without locking in to any specific language. We also will briefly discuss how it manages to improve localized language predictions and the challenges some transliteration system faces along with how we can tackle them.